This page has only limited features, please log in for full access.
Online formative assessments in e-learning systems are increasingly of interest in the field of education. While substantial research into the model and item design aspects of formative assessment has been conducted, few software systems embodied with a psychometric model have been proposed to allow us to adaptively implement formative assessments. This study aimed to develop an adaptive formative assessment system, called computerized formative adaptive testing (CAFT) by using artificial intelligence methods based on computerized adaptive testing (CAT) and Bayesian networks as learning analytics. CAFT can adaptively administer personalized formative assessment to a learner by dynamically selecting appropriate items and tests aligned with the learner’s ability. Forty items in an item bank were evaluated by 410 learners, moreover, 1000 learners were recruited for a simulation study and 120 learners were enrolled to evaluate the efficiency, validity, and reliability of CAFT in an application study. The results showed that, through CAFT, learners can adaptively take item s and tests in order to receive personalized diagnostic feedback about their learning progression. Consequently, this study highlights that a learning management system which integrates CAT as an artificially intelligent component is an efficient educational evaluation tool for a remote personalized learning service.
Younyoung Choi; Cayce McClenen. Development of Adaptive Formative Assessment System Using Computerized Adaptive Testing and Dynamic Bayesian Networks. Applied Sciences 2020, 10, 8196 .
AMA StyleYounyoung Choi, Cayce McClenen. Development of Adaptive Formative Assessment System Using Computerized Adaptive Testing and Dynamic Bayesian Networks. Applied Sciences. 2020; 10 (22):8196.
Chicago/Turabian StyleYounyoung Choi; Cayce McClenen. 2020. "Development of Adaptive Formative Assessment System Using Computerized Adaptive Testing and Dynamic Bayesian Networks." Applied Sciences 10, no. 22: 8196.
Purpose: The deterministic inputs, noisy “and” gate (DINA) model is a promising statistical method for providing useful diagnostic information about students’ level of achievement, as educators often want to receive diagnostic information on how examinees did on each content strand, which is referred to as a diagnostic profile. The purpose of this paper was to classify examinees of the Korean Medical Licensing Examination (KMLE) in different content domains using the DINA model.Methods: This paper analyzed data from the KMLE, with 360 items and 3,259 examinees. An application study was conducted to estimate examinees’ parameters and item characteristics. The guessing and slipping parameters of each item were estimated, and statistical analysis was conducted using the DINA model.Results: The output table shows examples of some items that can be used to check item quality. The probabilities of mastery of each content domain were also estimated, indicating the mastery profile of each examinee. The classification accuracy and consistency for 8 content domains ranged from 0.849 to 0.972 and from 0.839 to 0.994, respectively. As a result, the classification reliability of the cognitive diagnosis model was very high for the 8 content domains of the KMLE.Conclusion: This mastery profile can provide useful diagnostic information for each examinee in terms of each content domain of the KMLE. Individual mastery profiles allow educators and examinees to understand which domain(s) should be improved in order to master all domains in the KMLE. In addition, all items showed reasonable results in terms of item parameters.
Younyoung Choi; Dong Gi Seo. Estimation of item parameters and examinees’ mastery probability in each domain of the Korean Medical Licensing Examination using a deterministic inputs, noisy “and” gate (DINA) model. Journal of Educational Evaluation for Health Professions 2020, 17, 35 .
AMA StyleYounyoung Choi, Dong Gi Seo. Estimation of item parameters and examinees’ mastery probability in each domain of the Korean Medical Licensing Examination using a deterministic inputs, noisy “and” gate (DINA) model. Journal of Educational Evaluation for Health Professions. 2020; 17 ():35.
Chicago/Turabian StyleYounyoung Choi; Dong Gi Seo. 2020. "Estimation of item parameters and examinees’ mastery probability in each domain of the Korean Medical Licensing Examination using a deterministic inputs, noisy “and” gate (DINA) model." Journal of Educational Evaluation for Health Professions 17, no. : 35.
Owing to its potentially far-reaching impact on a large population, an educational policy may lead to unintended consequences beyond the educational area. The High School Equalization Policy (HSEP), introduced into South Korea in the mid-1970s, is representative of such a policy. HSEP prohibits high school entrance exams and randomly assigns students to a high school near their residence. Despite its aim of ensuring equal opportunities in education for all students regardless of socio-economic status, a frequent criticism was that HSEP could prompt students’ families to move to a region near traditional elite high schools, which, in turn, would widen the gap in house prices between different regions. Thus, we conducted an empirical study to examine the secondary influence of the HSEP on the housing market via a difference-in-differences (DD) analysis. We used house price data from the Gangwon province, as the partial introduction of HSEP into the province allowed for a quasi-experimental study on the effect of HSEP. The result revealed that, contrary to expectations, the HSEP in Gangwon had the opposite spillover effect of reducing the gap of the average house prices by 5%~9% across regions.
GyeongCheol Cho; Younyoung Choi; Ji-Hyun Kim. Investigating the Unintended Consequences of the High School Equalization Policy on the Housing Market. Sustainability 2020, 12, 8496 .
AMA StyleGyeongCheol Cho, Younyoung Choi, Ji-Hyun Kim. Investigating the Unintended Consequences of the High School Equalization Policy on the Housing Market. Sustainability. 2020; 12 (20):8496.
Chicago/Turabian StyleGyeongCheol Cho; Younyoung Choi; Ji-Hyun Kim. 2020. "Investigating the Unintended Consequences of the High School Equalization Policy on the Housing Market." Sustainability 12, no. 20: 8496.
The sustainable computer-based evaluation system (SCE) is a scenario-based formative evaluation system, in which students are assigned a task during a course. The tasks include the diversity conditions in real-world scenarios. The goals of this system are learning to think as a professional in a certain discipline. While the substantive, psychological, instructional, and task developmental aspects of the assessment have been investigated, few analytic methods have been proposed that allow us to provide feedback to learners in a formative way. The purpose of this paper is to introduce a framework of a learning analytic method including (1) an assessment design through evidence-centered design (ECD), (2) a data mining method using social network analysis, and (3) an analytic method using a Bayesian network. This analytic framework can analyze the learners’ performances based on a computational psychometric framework. The tasks were designed to measure 21st century learning skills. The 250 samples of data collected from the system were analyzed. The results from the social network analysis provide the learning path during a course. In addition, the 21st century learning skills of each learner were inferred from the Bayesian network over multiple time points. Therefore, the learning analytics proposed in this study can offer the student learning progression as well as effective feedback for learning.
Younyoung Choi; Young Cho. Learning Analytics Using Social Network Analysis and Bayesian Network Analysis in Sustainable Computer-Based Formative Assessment System. Sustainability 2020, 12, 7950 .
AMA StyleYounyoung Choi, Young Cho. Learning Analytics Using Social Network Analysis and Bayesian Network Analysis in Sustainable Computer-Based Formative Assessment System. Sustainability. 2020; 12 (19):7950.
Chicago/Turabian StyleYounyoung Choi; Young Cho. 2020. "Learning Analytics Using Social Network Analysis and Bayesian Network Analysis in Sustainable Computer-Based Formative Assessment System." Sustainability 12, no. 19: 7950.
부동산분석(Journal of Real Estate Analysis)
Younyoung Choi. A Study on the Effects of Community Revitalization Programs and Satisfaction therewith on Choosing Residential Facilities for Older Adults. Journal of Real Estate Analysis 2019, 5, 95 -107.
AMA StyleYounyoung Choi. A Study on the Effects of Community Revitalization Programs and Satisfaction therewith on Choosing Residential Facilities for Older Adults. Journal of Real Estate Analysis. 2019; 5 (1):95-107.
Chicago/Turabian StyleYounyoung Choi. 2019. "A Study on the Effects of Community Revitalization Programs and Satisfaction therewith on Choosing Residential Facilities for Older Adults." Journal of Real Estate Analysis 5, no. 1: 95-107.
Purpose: The dimensionality of examinations provides empirical evidence of the internal test structure underlying the responses to a set of items. In turn, the internal structure is an important piece of evidence of the validity of an examination. Thus, the aim of this study was to investigate the performance of the DETECT program and to use it to examine the internal structure of the Korean nursing licensing examination. Methods: Non-parametric methods of dimensional testing, such as the DETECT program, have been proposed as ways of overcoming the limitations of traditional parametric methods. A non-parametric method (the DETECT program) was investigated using simulation data under several conditions and applied to the Korean nursing licensing examination. Results: The DETECT program performed well in terms of determining the number of underlying dimensions under several different conditions in the simulated data. Further, the DETECT program correctly revealed the internal structure of the Korean nursing licensing examination, meaning that it detected the proper number of dimensions and appropriately clustered the items within each dimension.Conclusion: The DETECT program performed well in detecting the number of dimensions and in assigning items for each dimension. This result implies that the DETECT method can be useful for examining the internal structure of assessments, such as licensing examinations, that possess relatively many domains and content areas.
Dong Gi Seo; Younyoung Choi; Sun Huh. Usefulness of the DETECT program for assessing the internal structure of dimensionality in simulated data and results of the Korean nursing licensing examination. Journal of Educational Evaluation for Health Professions 2017, 14, 32 .
AMA StyleDong Gi Seo, Younyoung Choi, Sun Huh. Usefulness of the DETECT program for assessing the internal structure of dimensionality in simulated data and results of the Korean nursing licensing examination. Journal of Educational Evaluation for Health Professions. 2017; 14 ():32.
Chicago/Turabian StyleDong Gi Seo; Younyoung Choi; Sun Huh. 2017. "Usefulness of the DETECT program for assessing the internal structure of dimensionality in simulated data and results of the Korean nursing licensing examination." Journal of Educational Evaluation for Health Professions 14, no. : 32.